Abstract: The main aim of this study was to create a model of tacit collusion that could be used to detect such collusion. The secondary aim was to provide suggestions on how to curb tacit collusion, given the different variables that affect it. The following variables were investigated to gauge the extent of their effect on tacit collusion: demand; firms’ costs; and, finally, the number of firms’ and buyers’ suspicions regarding collusion among firms. Given the complexity of the interactions between firms and buyers, resulting from firms and buyers attempting to follow their individual rules, an agent-based model was used in the study. Agent-based models are a relatively new way of modelling complex interactions while incorporating a multitude of variables. In this way, agent-based models have an advantage over econometric models or standard simulation models, which are incapable of handling such complexity. Results from the agent-based model were consistent with economic theory and suggested that the model was calibrated correctly. A key finding was that pricing leadership behaviour occurs between firms, but that this behaviour may differ, depending on the varying attributes of the different firms. We were able to derive patterns of each such behaviour. In doing so, it was proven, in principle, that tacit collusion can be detected, and, designing an automated system to identify it was indeed possible.